Abstract
Metabarcoding of bulk community samples is a powerful tool to characterize marine softbottom macrofaunal communities, but high-quality taxonomic assignment is dependent on adequate sequence coverage in taxonomic databases. Here, our main aim was to advance metabarcoding as a complement to benthic morphological taxonomy in biodiversity inventories on the Norwegian Continental Shelf (NCS). We used morphological taxonomy, barcoding, and metabarcoding for two objectives, namely to (1) increase macrofauna barcode coverage for a selection of species, and (2) provide an in-depth comparison of morphology and metabarcoding data from mock bulk samples of softbottom macrofauna. We used morphological taxonomy to identify 257 morphotaxa from 32 sieved grab sampling stations at eight areas on the NCS. For the first objective (barcoding), 45 species (95 specimens) were selected from these 32 stations based on incomplete sequence coverage in online repositories, obtaining barcodes for 25 (cytochrome oxidase subunit 1, COI), 35 (18S rDNA), and 24 (28S rDNA) species. Results typically showed an increase in taxonomic assignment of 4-5 ranks in the subsequent metabarcoding data for these particular species. For the second objective (metabarcoding), mock bulk samples with a known taxonomic composition including Annelida, Arthropoda, Mollusca and a single brachiopod, were sequenced using the COI and 18S rDNA V1-V2 partitions from a subset of eight stations from three of the areas. COI Barcode of Life Data System (BOLD) and MIDORI2 assignment with some additional manual sequence curation recovered 100 distinct species-rank taxa compared to 120 species-rank taxa (152 taxa total) from morphology based taxonomic identification. Assignment of 18S rDNA using SILVA recovered 29 unique species including 13 not found in the COI data. Annelida, Arthropoda, and Mollusca were all well-represented in metabarcoding data, and abundance biases were associated with disparate species in a range of clades. Taxonomic congruence was high at high rank, but in some cases species assignments resolved as genus only or sibling species to those identified by morphological taxonomy even when present in one of the databases used. Potential explanations include species genotype variation, putative species complexes and remnant sequencing artifacts. The study findings show the potential of metabarcoding in an area with relatively high taxonomic database coverage. Integrating metabarcoding datasets can increase biodiversity inventory pace and uncover hidden biodiversity, but performance is dependent on database coverage, highlighting the importance of barcoding efforts in biodiversity studies, and metabarcoding-based inventories need to be critically examined by taxonomic expertise.